

    \filetitle{regress}{Ordinary or weighted least-square regression}{tseries/regress}

	\paragraph{Syntax}\label{syntax}

\begin{verbatim}
[B,BStd,E,EStd,YFit,Range,BCov] = regress(Y,X)
[B,BStd,E,EStd,YFit,Range,BCov] = regress(Y,X,Range,...)
\end{verbatim}

\paragraph{Input arguments}\label{input-arguments}

\begin{itemize}
\item
  \texttt{Y} {[} tseries {]} - Tseries object with independent (LHS)
  variables.
\item
  \texttt{X} {[} tseries{]} - Tseries object with regressors (RHS)
  variables.
\item
  \texttt{Range} {[} numeric {]} - Date range on which the regression
  will be run; if not specified, the entire range available will be
  used.
\end{itemize}

\paragraph{Output arguments}\label{output-arguments}

\begin{itemize}
\item
  \texttt{B} {[} numeric {]} - Vector of estimated regression
  coefficients.
\item
  \texttt{BStd} {[} numeric {]} - Vector of std errors of the estimates.
\item
  \texttt{E} {[} tseries {]} - Tseries object with the regression
  residuals.
\item
  \texttt{EStd} {[} numeric {]} - Estimate of the std deviation of the
  regression residuals.
\item
  \texttt{YFit} {[} tseries {]} - Tseries object with fitted LHS
  variables.
\item
  \texttt{Range} {[} numeric {]} - The actually used date range.
\item
  \texttt{bBCov} {[} numeric {]} - Covariance matrix of the coefficient
  estimates.
\end{itemize}

\paragraph{Options}\label{options}

\begin{itemize}
\item
  \texttt{'constant='} {[} \texttt{true} \textbar{}
  \emph{\texttt{false}} {]} - Include a constant vector in the
  regression; if true the constant will be placed last in the matrix of
  regressors.
\item
  \texttt{'weighting='} {[} tseries \textbar{} \emph{empty} {]} -
  Tseries object with weights on the observations in the individual
  periods.
\end{itemize}

\paragraph{Description}\label{description}

This function calls the built-in \texttt{lscov} function.

\paragraph{Example}\label{example}


